





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


a__    :		int      						=     {
    'configuration_conditional_detr': [
        'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'ConditionalDetrConfig',
        'ConditionalDetrOnnxConfig',
    ]
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					a__    :		List[str]      						=     ['ConditionalDetrFeatureExtractor']
					a__    :		int      						=     ['ConditionalDetrImageProcessor']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					a__    :		Optional[int]      						=     [
					    'CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'ConditionalDetrForObjectDetection',
					    'ConditionalDetrForSegmentation',
					    'ConditionalDetrModel',
					    'ConditionalDetrPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_conditional_detr import (
					    CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    ConditionalDetrConfig,
					    ConditionalDetrOnnxConfig,
					)

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_conditional_detr import ConditionalDetrFeatureExtractor
										from .image_processing_conditional_detr import ConditionalDetrImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_conditional_detr import (
										    CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ConditionalDetrForObjectDetection,
										    ConditionalDetrForSegmentation,
										    ConditionalDetrModel,
										    ConditionalDetrPreTrainedModel,
										)

else:
					import sys

					a__    :		Optional[int]      						=     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


def       _SCREAMING_SNAKE_CASE   (						_lowerCamelCase					:     int)   ->       int:






							'''simple docstring'''





							__UpperCamelCase      :  Tuple       =   1
							for i in range(1		,    num + 1):
														fact *= i
							return fact




def       _SCREAMING_SNAKE_CASE   (						_lowerCamelCase					:     int)   ->       int:






							'''simple docstring'''





							__UpperCamelCase      :  Dict       =   0
							while number > 0:
														__UpperCamelCase      :  List[Any]       =   number % 10
														sum_of_digits += last_digit
														__UpperCamelCase      :  List[Any]       =   number // 10  # Removing the last_digit from the given number
							return sum_of_digits




def       _SCREAMING_SNAKE_CASE   (						_lowerCamelCase					:     int = 100)   ->       int:






							'''simple docstring'''





							__UpperCamelCase      :  Optional[Any]       =   factorial(_lowerCamelCase)
							__UpperCamelCase      :  Tuple       =   split_and_add(_lowerCamelCase)
							return result


if __name__ == "__main__":
		print(solution(int(input('Enter the Number: ').strip())))